Robert Steven Nerem

Observations of mass changes in the cryosphere are critical to understanding the impact of climate change and constraining global projections of sea-level rise. Observations from satellite gravimetry missions, satellite altimetry, and Surface Mass Balance (SMB) models provide differing estimates of mass change at different temporal and spatial scales making intercomparison challenging. GRACE-FO is equipped with two sensors to track the inter-satellite distance; a baseline K-band microwave ranging system (KBR) and an experimental Laser Ranging Interferometer (LRI). The improved ranging precision of the LRI enables Line-of-Sight Gravity Difference (LGD) observations with substantially greater sensitivity to short-wavelength gravity signals than is possible with the KBR and at a range of temporal scales. Building on previous work demonstrating enhanced high-frequency sensitivity over Greenland and Antarctica, we apply LGD as a validation tool for GRACE-FO mascon products, ICESat-2-derived mass-change estimates, and two versions of the RACMO SMB model over the same region. This tests products commonly used for mass-change observations in the cryosphere over a range of spatial and temporal scales. LRI-derived LGD uniquely enables an independent direct frequency domain validation of the effective gravity signals from different mas change products without the limiting effects of temporal aliasing. By forward modeling gravity from monthly mass-change solutions and comparing the resulting synthetic LGD with LRI LGD observations, we assess the ability of different mass-change products to recover signals over multiple spatial and temporal scales. The results demonstrate that the effective spatial resolution of mass-change products is not characterized by a single spatial scale but instead depends on the interaction between the magnitude of the mass-change signal, the spatial and temporal scale of mass changes, and the measurement or modeling technique. This validation is particularly important for the cryosphere where understanding the effective spatial and temporal resolution of products can change the interpretation of the data. Validation of mass-change products using LGD provides a new approach for evaluating existing mass-change products in Greenland and Antarctica as well as guiding the development of future mass-change products.

Recent advances in optical clock technology offer the possibility of directly sensing differences in the Earth’s gravitational potential through frequency comparisons between satellites. This study investigates the performance of different satellite formation-flying architectures for recovering the time-variable gravity field using optical clock measurements.Four formation geometries are considered: a GRACE-like along-track configuration and three multidirectional formations, namely Cartwheel, Pendulum, and Helix. We performed a simulation analysis over 2016-2018 and synthesized the observable, geopotential difference, based on Hydrology, Icesheet and Solid Earth components of the v3 of the ESA Earth System Model. The observations were then contaminated with AOD1B error (from AOe07) and various clock noise levels from 10-17 to 10-20. We estimated monthly spherical harmonic solutions to degree 60, and evaluated the results in the spectral and spatial domain, as well as through examining timeseries of terrestrial water storage changes and icesheet mass change. The results show that formation geometry strongly influences the quality and spatial characteristics of time-variable gravity solutions. Our results show that a clock noise level of 10-19-10-20 is required to reliably recover time-variable gravity fields. Compared with the GRACE-like formation, multidirectional formations such as the Pendulum provide substantially improved solutions, both in terms of error magnitude and isotropy, making the errors easier to mitigate with a simple Gaussian filter. The performance of formation-flying missions depends strongly on clock noise, highlighting an important interplay between measurement precision and formation geometry. As clock performance improves, the influence of constellation geometry becomes increasingly important, with the Pendulum and Helix configurations showing particularly promising time-variable gravity recovery capabilities, especially at smaller spatial scales.

A widely accepted global model of glacial isostatic adjustment (GIA) is based on ICE‐6G ice loading and 1D‐viscosity model VM5a, a viscosity profile which remains at odds with mantle convection constraints such as from geoid modeling. We explore 3D‐viscosity variations in models of GIA and show that a model with lateral viscosity variations (LVVs) scaled from seismic tomography and lower mantle viscosity compatible with mantle convection constraints (∼30 times upper mantle viscosity) significantly reduces the misfit to relative sea level (∼40%), (60%), and polar motion (75%) while incurring only a small misfit penalty (∼5%) for GNSS‐uplift compared to VM5a, which has lower mantle viscosity ∼6 times upper mantle viscosity. Regional results exhibit additional tradeoffs but indicate that comparable solutions might be found with additional model refinement. The origin of a longstanding disagreement on lower mantle viscosity may thus be resolved by accounting for LVVs in models of GIA.

Patterns of sea level rise (SLR) and surface warming are tightly coupled, though strong S/N in SLR makes it ideal for identifying forced responses. While climate model ensembles provide an estimate of the forced SLR pattern, standard-resolution models poorly resolve key components of the coupled climate response, including ocean eddies and atmospheric and oceanic fronts. The importance of these small-scale features to regional SLR trends constitutes a major uncertainty in current simulations. Here, the improvements provided through high-resolution (HR) modeling are demonstrated using the recently released MESACLIP experiment, a 10-member ensemble spanning 1920-2100 that is unique for its HR atmospheric (0.25º) and oceanic (0.1º) components. Through comparison with standard-resolution simulations, including a nominal 1º version of the model used in MESACLIP, a fundamental alteration in both the pattern and magnitude of forced regional SLR in the MESACLIP simulations is demonstrated. Agreement between 30-year simulated trends and satellite altimetry is greatly improved and altimeter-era emergence of a La Niña-like forced response is identified in the Pacific and Southern Oceans. These findings suggest that forcing contributes significantly to the ongoing La Niña-like changes in the Pacific ocean and that significant improvements in forced climate change patterns, including those in regional SLR, can be realized through HR climate model ensembles.

Understanding how ocean tides propagate within estuaries and rivers is important for quantifying upstream tidally influenced water level variability and flood risk under sea level rise. Conventional observations from tide gauges provide accurate tidal estimates, but are spatially sparse and confined to fixed locations, but have limited ability to resolve lateral and cross-channel structure. In this study, we use high-resolution wide-swath altimetry (100m L2 HR Raster) from the Surface Water and Ocean Topography (SWOT) Satellite mission to directly observe the two-dimensional spatial structure of the M2 tidal variability across estuarine and riverine systems. We characterize how tidal signals evolve spatially as they propagate inland, including regions of amplification, reduced wave speed and spatial gradients coincident with variations in channel geometry. The results reveal coherent spatial structures that are not captured by along-channel or point-based analysis and identify locations where tidal-river interactions may increase sensitivity to background sea level changes and compound flooding. We identify localized regions where the tidal wave exhibits a slowdown in propagation concurrent with an increase in amplitude, indicating spatially confined zones with a convergence of tidal energy. These regions represent sensitive locations where long wavelength disturbances, such as storm surges, may amplify as they propagate inland.

Since 1993, satellite altimeters have been mapping sea level changes globally, revealing both the global mean rate and detailed patterns of regional variations. The global mean rate is well studied, closely linked to global energy and water cycles, while regional patterns are influenced by a complex mix of internal climate dynamics and external factors like greenhouse gases and aerosols. Yet, a synthesis of these regional patterns using a comprehensive diagnostic approach has been lacking. Our research addresses this gap by integrating oceanic and atmospheric observations with large ensembles of state‐of‐the‐art global climate models. This approach sheds new light upon the mechanisms behind basin‐scale sea level patterns worldwide. A key finding is the dominant influence of wind forcing, particularly Ekman and Sverdrup dynamics, in shaping sea level changes from the tropics to higher latitudes. We find that the pattern of sea level rise since 1993 is primarily driven by wind‐induced changes in ocean circulation, which can affect sea surface height through ocean mass and heat distribution. Interestingly, these wind‐driven changes are not just products of internal climate variability; most of the observed patterns are recovered by global climate model projections driven by historical anthropogenic forcings, and single‐forcing experiments provide further insight into which forcings are responsible for various features in the satellite altimetry record. Understanding the drivers of regional sea level rise, including differentiating anthropogenic signals from natural variability, is essential for effectively adapting to climate change impacts on global infrastructure and society.

Coastal planning, mitigation, and adaptation efforts are increasingly relying on sea-level projections generated by physical models. However, the large uncertainties in these projections pose a challenge for policy makers. Here we provide an overview of the sources of uncertainty in model projections of sea-level change over decadal-to-centennial timescales and we offer perspectives on the use of observations to narrow uncertainties. We propose several directions for future research, including improvements in emulation techniques, more systematic quantification of uncertainty structure within both observations and models, lengthening observational records of processes, and expanding collaboration across physical and social sciences. Advancements in these areas are urgently needed, as the next phase of the Intergovernmental Panel on Climate Change assessment report cycle gets underway.

We perform a quadratic extrapolation of sea level on a regional scale based on satellite altimeter observations spanning 1993.0–2023.0, including corrections for natural climate variability, vertical land motion, and a rigorous assessment of the uncertainties associated with serially correlated formal errors, glacial isostatic adjustment, and satellite altimeter measurement errors. The extrapolations are data‐driven and show the trajectory of relative sea level (RSL) over the last 30 years extrapolated into the future. These extrapolations suggest that RSL rise in 2050 relative to 2020 will be 22 ± 5 cm in the North Pacific, 19 ± 6 cm in the North Atlantic, 17 ± 4 cm in the South Atlantic, 15 ± 5 cm in the Indian Ocean, 14 ± 5 cm in the South Pacific, 13 ± 5 cm in the Tropical Pacific, and 12 ± 4 cm in the Southern Ocean. The regional results may differ from each other by more than 80% and differ significantly from the extrapolated global mean sea level rise of 16 ± 4 cm in most cases. The errors in these regional extrapolations are relatively narrow, and we show significant overlap with the regional projections from the most recent IPCC Sixth Assessment Report. The results provide an additional line of evidence when considering how representative the range of climate model projections are in describing near‐term sea level rise and highlight the significance of regional variations in estimates of future sea level.

The time history of the Earth's dynamic oblateness, or , is a unique climate data record, with its estimation from satellite laser ranging (SLR) tracking data beginning in 1976. Due to its impact on variations in length of day (LOD), the long‐term time series is frequently applied to LOD studies and their contributions, which include tidal friction, glacial isostatic adjustment, ice melt, sea level change, and the angular momentum exchange between the fluid outer core and the mantle. Previous studies demonstrated that the accurate recovery of requires the use of time variable gravity models from GRACE when processing the SLR tracking data. However, no reliable models exist prior to GRACE's 2002 launch, calling into to question the accuracy and utility of the pre‐GRACE estimates. Here we present a new approach to accurately recover without gravity modeling, resulting in the first fully consistent long‐term solution for climate studies.